Datasets:

ruili3
/

pointdit_occ

+---
+license: other
+tags:
+- point-cloud
+- flow-matching
+- scannetpp
+---
+# PointDiT global-uniform-512d12
+Image-to-point-cloud flow matching model (`global_image_point_joint`): frozen DINOv3 ViT-B/16 image encoder + 512-dim, 12-layer point decoder (153.6M params), 8192 points per image, trained on ScanNet++ `img_full_gt` (721 scenes / 71,712 images).
+Code: `experiments/global_point/` on branch `global-uniform-512d12` of the PointDiT repo.
+## Files
+- `global-uniform-512d12/checkpoint-last.pth` — final checkpoint (epoch 15, step 16,815). Full training checkpoint: `model` (incl. frozen DINOv3), `decoder_ema`, `optimizer`, `config`, RNG states; can be passed to `--resume`. sha256 `f71698c5e8a8e6aa2e6b7a087dec9180dcf068318a321786b0d77b3263e50b35`.
+- `global-uniform-512d12/eval/eval-global512-{raw,ema}-steps{3,10,50}/` — `metrics.json` (protocol + image/scene/per-scene means) and `visuals/`: 135 sampled val images (first/middle/last image of each of the 45 scenes) with the input RGB (`*.rgb.jpg`) and GT + predicted point clouds (`*.points.js`, base64 float32 xyz). Open `visuals/index.html` locally (after downloading the folder) to view them.
+## Training
+4×A800, global batch 64, lr 1e-4 (1 warmup epoch), AdamW wd 0.05, 15 epochs, uniform t sampler, noise scale 2.0, EMA 0.9999, bf16 autocast.
+## Evaluation (protocol `official_val_raw100_global_v4`)
+ScanNet++ official val, 4,479 images / 45 scenes (no overlap with training scenes), bf16, seed 20261007, 8192 points, no test-time alignment. Image mean over all images (scene mean is nearly identical, see `metrics.json`).
+`cd2`, `acc`, `comp`: lower is better; F@τ: higher is better; `radius_ratio`: predicted/GT mean radius (1 = correct scale).
+| weights | steps | cd2 | acc | comp | F@0.02 | F@0.05 | F@0.1 | radius_ratio |
+|---|---|---|---|---|---|---|---|---|
+| raw | 3 | 0.1844 | 0.1793 | 0.2929 | 0.030 | 0.138 | 0.263 | 0.430 |
+| raw | 10 | 0.0701 | 0.1428 | 0.1283 | 0.045 | 0.256 | 0.506 | 0.802 |
+| raw | 50 | 0.0620 | 0.1375 | 0.1122 | 0.048 | 0.267 | 0.551 | 0.961 |
+| ema | 3 | 0.0902 | 0.1581 | 0.1595 | 0.037 | 0.216 | 0.433 | 0.694 |
+| ema | 10 | 0.0827 | 0.1423 | 0.1564 | 0.039 | 0.230 | 0.470 | 0.924 |
+| ema | 50 | 0.1050 | 0.1421 | 0.2014 | 0.035 | 0.183 | 0.393 | 0.996 |
+Best: raw weights, 50 steps. EMA (decay 0.9999) has seen only ~17k steps and gets worse at 50 steps.
+The RGB images and GT point clouds in `visuals/` are derived from ScanNet++ and are subject to the ScanNet++ terms of use.

global-uniform-512d12/eval/eval-global512-ema-steps10/metrics.json ADDED Viewed

	@@ -0,0 +1,1008 @@

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+}

global-uniform-512d12/eval/eval-global512-ema-steps10/visuals/00000.points.js ADDED Viewed